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Marriott Marquis, Grand Ballroom 4
American Economic Association
New Research on School Choice: The Role of Parental Preferences, Housing Search, and Assignment Mechanisms
Saturday, Jan. 4, 2020 10:15 AM - 12:15 PM (PDT)
- Chair: Justine Hastings, Brown University
Housing Search Frictions: Evidence from Detailed Search Data and a Field Experiment
AbstractWe combine data on low-income households' housing search behavior with a randomized information-provision experiment to examine the role of information frictions in the lack of moves by low-income households to areas with high-quality schools. We find that providing information about school quality to online listings at a key point in households' search causes them to move to areas with higher school quality. We use the experiment to estimate a dynamic model of households' search and location choices that incorporates subjective beliefs about the distribution of school quality and other amenities. We find that treated households value a roughly 10-percentile increase in our school quality measure the same as a 20-minute reduction in distance to city center; if we had ignored information frictions, we would have estimated a value of less than one minute.
What Do Families Want from Schools? Evidence from Real Choices and a Survey of Choosers
AbstractWe analyze families' preferences for school characteristics using data from an urban school district in the Western United States. This district operates a public school choice system with a centralized school assignment process. Parents rank the public schools in the district and an algorithm assigns students to schools based on parental preferences, school capacity constraints and district priorities. In Fall 2018 we surveyed parents as they made these rankings. Our survey asked parents for their beliefs about the characteristics of the schools they were choosing and their beliefs about their children’s outcomes were they to attend these schools. The survey also include a discrete choice experiment that asked parents to compare hypothetical schools. We match these survey data to administrative data on parents’ real choices and other information from student records, including ethnicity, proxies for socio-economic status and test scores. We use these matched data to analyse parents' preferences for school characteristics.
The Effects of Affirmative Action on Targeted and Non-Targeted Students: Evidence from Low-Income Priorities in Paris High School
AbstractSince 2008, school choice in Paris has an income-based affirmative action component granting low-income students preferential treatment in high school admissions. This policy is implemented as part of a centralized school choice procedure that assigns students to public schools based on a version of the Gale-Shapley deferred acceptance mechanism. Students' priorities are determined using a point system that takes into account students' academic performance and their district of residence. Low-income students, representing approximately 20 percent of high school entrants, are awarded a large bonus which gives them full priority at all public high schools within their district. We exploit the introduction of this bonus in 2008 as a natural experiment to investigate the effects of income-based affirmative action on the high school outcomes and college access of both targeted and non-targeted students. Using comprehensive administrative data on students' pathways from middle school to postsecondary education over the period 2004-2016, we implement a difference-in-differences strategy in which we compare students in Paris to those living in its close suburbs, where no affirmative action policy was implemented during the period. Detailed data from Paris’ centralized school choice procedure is used to determine whether a student (i) gained access to a more preferred school a result of the bonus (displacers), (ii) was displaced and assigned to a less preferred school (displacees) or (iii) would have been assigned to the same school had the bonus not been in place. Comparing the treatment effects across these different groups of students allows us to separately identify the policy’s direct effects from its indirect effects arising from the induced change in peer composition.
Douglas O. Staiger,
University of California-Berkeley
- H4 - Publicly Provided Goods
- I2 - Education and Research Institutions